Go-Jek, Indonesia’s first billion-dollar startup, has seen an incredible amount of growth in both users and data over the past two years. Many of the ride-hailing company's services are backed by machine learning models. Models range from driver allocation, to dynamic surge pricing, to food recommendation, and process millions of bookings every day, leading to substantial increases in revenue and customer retention.
Building a feature platform has allowed Go-Jek to rapidly iterate and launch machine learning models into production. The platform allows for the creation, storage, access, and discovery of features. It supports both low latency and high throughput access in serving, as well as high volume queries of historic feature data during training. This allows Go-Jek to react immediately to real world events.
Find out how Go-Jek implemented their feature platform, and other lessons learned scaling machine learning.